The etiology of many of our most serious social and medical problems, such as mental illness, cardiovascular disease and alcohol and drug abuse, appear very complex. Many currently funded research projects are collecting data from groups of relatives such as nuclear families, twin and adoptees in order to examine the role and importance of genetic factors in disease. Yet software for the analysis of these data, which often include longitudinal and multivariate components in additional to family structure, are inadequate. We aim to develop a comprehensive user-friendly resource for the statistical analysis of these data. Computational routines for matrix algebra, optimization and numerical integration will be interfaced to radically simplify specifications large-scale multivariate models and to enable specification of complex expressions for the likelihood of observed data. We will create a powerful menu-driven visual interface for modeling and analysis that will minimize user error and maximize flexibility. Data analysis will be streamlined throughout, from the reading of data, to local or remote computation, to the production of tables and figures of publication. This resource will be developed in preparation for collaborative data analysis on five currently funded projects spanning: cardiovascular disease, anxiety and depression, juvenile conduct disorder, drug and alcohol use and depression, and panic disorders, phobias, eating disorders, and schizophrenia. Use of the software will be taught at national and international workshops on methodology for twin and family studies, where further collaborative research initiatives will be identified. The code will be ported to a variety of platforms. A moderate level of support will be provided for users at other institutions worldwide.